Period: Last 7 Days (Nov 30 - Dec 07, 2025)
Generated: 2025-12-07
381
7
74
328
796
55
10
Total Tickets Created: 297
Total Tickets Solved: 196
| Date | Created | Solved |
|---|---|---|
| 1 Dec 25 | 88 | 47 |
| 2 Dec 25 | 64 | 49 |
| 3 Dec 25 | 67 | 48 |
| 4 Dec 25 | 44 | 26 |
| 5 Dec 25 | 33 | 26 |
| 6 Dec 25 | 1 | 0 |
| Channel | Created | Solved |
|---|---|---|
| Messaging | 46 | 172 |
| 40 | 152 | |
| Web | 12 | 47 |
Total Agents: 7
Total Solved Tickets: 381
Average Satisfaction Score: 74.2%
| Agent Name | Solved Tickets | First Reply Time (hrs) | Resolution Time (hrs) | Satisfaction Score (%) | One-Touch Tickets (%) |
|---|---|---|---|---|---|
| Neo | 124 | 0.32 | 1.53 | 83.3% | 65.3% |
| Esther | 86 | 0.12 | 0.80 | 75.0% | 33.7% |
| Cristina | 62 | 0.22 | 0.98 | 100.0% | 45.2% |
| Jason | 53 | 0.35 | 1.37 | 62.5% | 41.5% |
| Lilly | 34 | 0.30 | 19.82 | N/A | 32.4% |
| John | 21 | 0.70 | 40.47 | 50.0% | 28.6% |
| Michael | 1 | 0.70 | 0.70 | N/A | 100.0% |
Total Solved Tickets: 328
Total Agent Replies: 796
Average Daily Solved: 54.7
Average Daily Replies: 132.7
| Date | Solved Tickets | Agent Replies | Avg Replies per Ticket |
|---|---|---|---|
| 01 Dec 25 | 93 | 183 | 1.97 |
| 02 Dec 25 | 61 | 149 | 2.44 |
| 03 Dec 25 | 79 | 212 | 2.68 |
| 04 Dec 25 | 39 | 97 | 2.49 |
| 05 Dec 25 | 55 | 134 | 2.44 |
| 06 Dec 25 | 1 | 21 | 21.00 |
Average Satisfaction Score: 74.2%
Agents with Satisfaction Data: 5
⚠️ Bad Satisfaction Tickets: 10
• Top Performer: Neo solved 124 tickets with 83.3% satisfaction. Consider sharing best practices with the team.
• Support Needed: John have satisfaction scores below 60%. Schedule coaching sessions to improve customer interactions.
• Efficiency Opportunity: Several agents have low one-touch ticket rates. Focus on first-contact resolution training to reduce ticket volume.
• Volume Management: Average 54.7 tickets solved per day. Monitor capacity and ensure adequate staffing for peak periods.
• Quality Focus: 10 tickets received bad satisfaction ratings. Review these cases to identify common issues and improve resolution quality.
• Maintain Excellence: Team satisfaction score of 74.2% is strong. Continue current practices and recognize top performers.
• Weekly Action Items:
• 1. Review individual agent performance with each team member
• 2. Identify and address any recurring customer issues
• 3. Optimize workload distribution based on agent strengths
• 4. Schedule training sessions for agents below performance targets
• 5. Celebrate top performers to maintain team morale